Author: Li Ang Zhang Publisher: ISBN: 9781977405159 Category : Computers Languages : en Pages : 70
Book Description
U.S. air superiority is being challenged by global competitors. In this report, the authors prototype a new artificial intelligence system to help develop and evaluate concepts of operations for the air domain.
Author: Koen H. Van Dam Publisher: Springer Nature ISBN: 3030945480 Category : Computers Languages : en Pages : 203
Book Description
This book constitutes the thoroughly refereed post-conference proceedings of the 21st International Workshop on Multi-Agent-Based Simulation, MABS 2021, held in May 2021 as part of AAMAS 2021. The conference was held virtually due to COVID 19 pandemic. The 14 revised full papers included in this volume were carefully selected from 23 submissions. The workshop focused on finding efficient solutions to model complex social systems, in such areas as economics, management, organizational and social sciences in general. In all these areas, agent theories, metaphors, models, analysis, experimental designs, empirical studies, and methodological principles, all converge into simulation as a way of achieving explanations and predictions, exploration and testing of hypotheses, better designs and systems and providing decision-support in a wide range of applications.
Author: Dilmurat Azimov Publisher: Springer Nature ISBN: 3031393031 Category : Technology & Engineering Languages : en Pages : 403
Book Description
This book showcases a collection of papers that present cutting-edge studies, methods, experiments, and applications in various interdisciplinary fields. These fields encompass optimal control, guidance, navigation, game theory, stability, nonlinear dynamics, robotics, sensor fusion, machine learning, and autonomy. The chapters reveal novel studies and methods, providing fresh insights into the field of optimal guidance and control for autonomous systems. The book also covers a wide range of relevant applications, showcasing how optimal guidance and control techniques can be effectively applied in various domains, including mechanical and aerospace engineering. From robotics to sensor fusion and machine learning, the papers explore the practical implications of these techniques and methodologies.
Author: John A. Warden, III Publisher: DIANE Publishing ISBN: 0788108093 Category : Languages : en Pages : 223
Book Description
One of the first analyses of the pure art of planning the aerial dimensions of war. Explores the complicated connection between air superiority and victory in war. Focuses on the use of air forces at the operational level in a theater of war. Presents fascinating historical examples, stressing that the mastery of operational-level strategy can be the key to winning future wars. 20 photos. Bibliography.
Author: Benjamin Franklin Cooling (III) Publisher: Washington, D.C. : Office of Air Force History, United States Air Force ISBN: Category : History Languages : en Pages : 722
Author: Yvonne R. Masakowski Publisher: Emerald Group Publishing ISBN: 1789738113 Category : Computers Languages : en Pages : 217
Book Description
Artificial Intelligence and Global Security: Future Trends, Threats and Considerations brings a much-needed perspective on the impact of the integration of Artificial Intelligence (AI) technologies in military affairs. Experts forecast that AI will shape future military operations in ways that will revolutionize warfare.
Author: Meiping Wu Publisher: Springer Nature ISBN: 9811694923 Category : Technology & Engineering Languages : en Pages : 3575
Book Description
This book includes original, peer-reviewed research papers from the ICAUS 2021, which offers a unique and interesting platform for scientists, engineers and practitioners throughout the world to present and share their most recent research and innovative ideas. The aim of the ICAUS 2021 is to stimulate researchers active in the areas pertinent to intelligent unmanned systems. The topics covered include but are not limited to Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and Its Application in Unmanned Systems. The papers showcased here share the latest findings on Unmanned Systems, Robotics, Automation, Intelligent Systems, Control Systems, Integrated Networks, Modeling and Simulation. It makes the book a valuable asset for researchers, engineers, and university students alike.
Author: David E. Johnson Publisher: Rand Corporation ISBN: 0833042416 Category : Study Aids Languages : en Pages : 265
Book Description
The relative roles of U.S. ground and air power have shifted since the end of the Cold War. At the level of major operations and campaigns, the Air Force has proved capable of and committed to performing deep strike operations, which the Army long had believed the Air Force could not reliably accomplish. If air power can largely supplant Army systems in deep operations, the implications for both joint doctrine and service capabilities would be significant. To assess the shift of these roles, the author of this report analyzed post?Cold War conflicts in Iraq (1991), Bosnia (1995), Kosovo (1999), Afghanistan (2001), and Iraq (2003). Because joint doctrine frequently reflects a consensus view rather than a truly integrated joint perspective, the author recommends that joint doctrine-and the processes by which it is derived and promulgated-be overhauled. The author also recommends reform for the services beyond major operations and campaigns to ensure that the United States attains its strategic objectives. This revised edition includes updates and an index.
Author: Robert L. Pfaltzgraff Publisher: DIANE Publishing ISBN: 1428992812 Category : Air power Languages : en Pages : 387
Book Description
This collection of essays reflects the proceedings of a 1991 conference on "The United States Air Force: Aerospace Challenges and Missions in the 1990s," sponsored by the USAF and Tufts University. The 20 contributors comment on the pivotal role of airpower in the war with Iraq and address issues and choices facing the USAF, such as the factors that are reshaping strategies and missions, the future role and structure of airpower as an element of US power projection, and the aerospace industry's views on what the Air Force of the future will set as its acquisition priorities and strategies. The authors agree that aerospace forces will be an essential and formidable tool in US security policies into the next century. The contributors include academics, high-level military leaders, government officials, journalists, and top executives from aerospace and defense contractors.
Author: William L. William L. Hamilton Publisher: Springer Nature ISBN: 3031015886 Category : Computers Languages : en Pages : 141
Book Description
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Author: Li Ang Zhang
Author: Koen H. Van Dam
Author: Dilmurat Azimov
Author: John A. Warden, III
Author: Benjamin Franklin Cooling (III)
Author: Yvonne R. Masakowski
Author: Meiping Wu
Author: David E. Johnson
Author: Robert L. Pfaltzgraff
Author: William L. William L. Hamilton